The Early Phases of Supernova 2020pni: Shock Ionization of the Nitrogen-enriched Circumstellar Material
Bibliographic record
Abstract
Abstract We present multiwavelength observations of the Type II SN 2020pni. Classified at ∼1.3 days after explosion, the object showed narrow (FWHM intensity <250 km s −1 ) recombination lines of ionized helium, nitrogen, and carbon, as typically seen in flash-spectroscopy events. Using the non-LTE radiative transfer code CMFGEN to model our first high-resolution spectrum, we infer a progenitor mass-loss rate of M ̇ = ( 3.5 – 5.3 ) × 10 − 3 M ⊙ yr −1 (assuming a wind velocity of v w = 200 km s −1 ), estimated at a radius of R in = 2.5 × 10 14 cm. In addition, we find that the progenitor of SN 2020pni was enriched in helium and nitrogen (relative abundances in mass fractions of 0.30–0.40 and 8.2 × 10 −3 , respectively). Radio upper limits are also consistent with dense circumstellar material (CSM) and a mass-loss rate of M ̇ > 5 × 10 − 4 M ☉ yr − 1 . During the initial 4 days after first light, we also observe an increase in velocity of the hydrogen lines (from ∼250 to ∼1000 km s −1 ), suggesting complex CSM. The presence of dense and confined CSM, as well as its inhomogeneous structure, indicates a phase of enhanced mass loss of the progenitor of SN 2020pni during the last year before explosion. Finally, we compare SN 2020pni to a sample of other shock-photoionization events. We find no evidence of correlations among the physical parameters of the explosions and the characteristics of the CSM surrounding the progenitors of these events. This favors the idea that the mass loss experienced by massive stars during their final years could be governed by stochastic phenomena and that, at the same time, the physical mechanisms responsible for this mass loss must be common to a variety of different progenitors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".